import covid19main

=== Dataset Structure ===
Shape (rows, columns): (350085, 67)

=== Column Check ===
Columns: ['iso_code', 'continent', 'location', 'date', 'total_cases', 'new_cases', 'new_cases_smoothed', 'total_deaths', 'new_deaths', 'new_deaths_smoothed', 'total_cases_per_million', 'new_cases_per_million', 'new_cases_smoothed_per_million', 'total_deaths_per_million', 'new_deaths_per_million', 'new_deaths_smoothed_per_million', 'reproduction_rate', 'icu_patients', 'icu_patients_per_million', 'hosp_patients', 'hosp_patients_per_million', 'weekly_icu_admissions', 'weekly_icu_admissions_per_million', 'weekly_hosp_admissions', 'weekly_hosp_admissions_per_million', 'total_tests', 'new_tests', 'total_tests_per_thousand', 'new_tests_per_thousand', 'new_tests_smoothed', 'new_tests_smoothed_per_thousand', 'positive_rate', 'tests_per_case', 'tests_units', 'total_vaccinations', 'people_vaccinated', 'people_fully_vaccinated', 'total_boosters', 'new_vaccinations', 'new_vaccinations_smoothed', 'total_vaccinations_per_hundred', 'people_vaccinated_per_hundred', 'people_fully_vaccinated_per_hundred', 'total_boosters_per_hundred', 'new_vaccinations_smoothed_per_million', 'new_people_vaccinated_smoothed', 'new_people_vaccinated_smoothed_per_hundred', 'stringency_index', 'population_density', 'median_age', 'aged_65_older', 'aged_70_older', 'gdp_per_capita', 'extreme_poverty', 'cardiovasc_death_rate', 'diabetes_prevalence', 'female_smokers', 'male_smokers', 'handwashing_facilities', 'hospital_beds_per_thousand', 'life_expectancy', 'human_development_index', 'population', 'excess_mortality_cumulative_absolute', 'excess_mortality_cumulative', 'excess_mortality', 'excess_mortality_cumulative_per_million']

=== Data Preview ===

	iso_code	continent	location	date	total_cases	new_cases	new_cases_smoothed	total_deaths	new_deaths	new_deaths_smoothed	...	male_smokers	handwashing_facilities	hospital_beds_per_thousand	life_expectancy	human_development_index	population	excess_mortality_cumulative_absolute	excess_mortality_cumulative	excess_mortality	excess_mortality_cumulative_per_million
0	AFG	Asia	Afghanistan	2020-01-03	NaN	0.0	NaN	NaN	0.0	NaN	...	NaN	37.746	0.5	64.83	0.511	41128772.0	NaN	NaN	NaN	NaN
1	AFG	Asia	Afghanistan	2020-01-04	NaN	0.0	NaN	NaN	0.0	NaN	...	NaN	37.746	0.5	64.83	0.511	41128772.0	NaN	NaN	NaN	NaN
2	AFG	Asia	Afghanistan	2020-01-05	NaN	0.0	NaN	NaN	0.0	NaN	...	NaN	37.746	0.5	64.83	0.511	41128772.0	NaN	NaN	NaN	NaN

3 rows × 67 columns

=== Missing Values Analysis ===
Null values per column:
iso_code                                        0
continent                                   16665
location                                        0
date                                            0
total_cases                                 37997
                                            ...  
population                                      0
excess_mortality_cumulative_absolute       337901
excess_mortality_cumulative                337901
excess_mortality                           337901
excess_mortality_cumulative_per_million    337901
Length: 67, dtype: int64

=== Handling Missing Values ===
Remaining rows after cleaning: 6759

C:\Users\hp\covid19main.py:69: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  df_clean['death_rate'] = (df_clean['total_deaths'] / df_clean['total_cases']) * 100

=== Analysis Complete ===